Fire Detection System Based-On Mobile Robots

The article describes a new auto-charging system designed to enhance successful docking rates for mobile robots while at the same time monitoring the status of the charging current between the mobile robot and the docking station. The communication interface of the mobile robot and the docking station uses a wireless RF interface. The docking station is designed with one active degree of freedom and two passive degrees of freedom. Users tune the location of the charging pins on the docking station to make it possible for the mobile robot to execute an auto-recharging process. The auto-recharging process uses multiple sensors and a laser range finder located on the mobile robot. The laser range finder searches for a landmark to guide the mobile robot towards the docking station. In the experiment, the power of the mobile robot is under its threshold value. The mobile robot transmits a charging command to the docking station via a wireless RF interface. The docking station transmits a location command back to the mobile robot via this wireless RF interface. The mobile robot uses its laser range finder to search for the landmark of the assigned docking station and programs a motion trajectory to move forward to the docking station. The docking station supplies a charging current to the mobile robot by means of a charger. The power detection module simultaneously detects the charging current and the voltage values of the charging process in both the docking station and the mobile robot. The system can monitor the status of the charging process between the docking station and the mobile robot at any time. The power of the mobile robot is enough to be detected by the power detection module. When the charging process is complete, the docking station turns off the charging current and triggers the mobile robot to leave the docking station via the wireless RF interface.

We present path-planning techniques for a multiple mobile robot system. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robot is an MCS-51 chip, and it acquires detection signals from sensors through I/O pins. It receives commands from the supervising computer via a wireless RF interface, and transmits the status of the robots to the supervising computer via a wireless RF interface. The mobile robot system is a module-based system, and contains a controller module (including two DC motors and drivers), an obstacle detection module, a voice module, a wireless RF module, an encoder module, and a compass detection module. We propose an evaluation method to arrange the position of the multiple mobile robot system, and develop a path-planning interface on the supervising computer. In the experimental results, the mobile robots were able to receive commands from the supervising computer, and to move their next positions according to the proposed method.

The article develops multi-pattern formation exchange using A* searching algorithm, and programs the shortest motion paths for mobile robots. The system contains an image recognition system, a motion platform, some wireless RF modules and five mobile robots. We use Otsu algorithm to recognize the variety 2D bar code to classify variety pattern, and control five mobile robots to execute formation exchange, and present the movement scenario on the motion platform. We have been developed some pattern formations according to game applications, such as hook pattern formation, T pattern formation, L pattern formation, rectangle pattern formation, sward pattern formation and so on, and develop the user interface of the multi-robot system to program motion paths for variety pattern formation exchange on the supervised computer. The supervised computer programs pattern formation exchange according to the image recognition results, and controls mobile robots moving on the motion platform via wireless RF interface. In the experimental results, mobile robots can receive the pattern formation command from the supervised computer, and change the original pattern formation to the assigned pattern formation on the motion platform, and avoid other mobile robots on real-time.

The article develops a vision based auto-recharging system for mobile robots, and programs a new docking processing to enhance successful rate. The system contains a docking station and a mobile robot. The docking station contains a docking structure, a control device, a charger and a detection device and a wireless RF interface. The mobile robot contains a power detection module (voltage and current), an auto-switch, a wireless RF interface, a control system and a camera. The docking structure is designed with one active degree of freedom and two passive degrees of freedom. The active degree of freedom can move forward to contact the recharging connect points that are arranged in the mobile robot. The two passive degrees of freedom can rotation in the Z-axis and use compression spring moving on various docking condition. In image processing, the mobile robot uses a webcam to capture the real-time image; and transmits the image signal to the computer via USB interface, and uses Otsu algorithm to recognize the position of the docking station. In the experiment results, the system had been successfully guided the mobile robot moving to the docking station using the proposed method.

The article presents multiple pattern formation control of the multi-robot system using A* searching algorithm, and avoids the collision points moving on the motion platform. We use speech recognition algorithm to decide the various pattern formations, and program mobile robots to present the movement scenario on the grid-based motion platform. We have been developed some pattern formations to be applied in game applications, such as long snake pattern formation, phalanx pattern formation, crane wing pattern formation, sword pattern formation, cone pattern formation and so on. The mobile robot contains a controller module, three IR sensor modules, a voice module, a wireless RF module, a compass module, and two DC servomotors. The controller of the mobile robot can acquire the detection signals from reflect IR sensor modules and the compass module, and decide the cross points of the aisle. The mobile robot receives the command from the supervised computer, and transmits the status of environment to the supervised computer via wireless RF interface. We develop the user interface of the multi-robot system to program motion paths for various pattern formation exchanges using the minimum displacement. Users can use speech to control the multiple mobile robots to execut pattern formation exchange. In the experimental results, users can speak the pattern formation. The speech recognition system receives the signal to decide the pattern formation. The multiple mobile robots can receive the pattern formation command from the supervised computer, and arrange the assigned pattern formation on the motion platform, and avoid other mobile robots.

Mobile robots are an efficient and useful application in the modern industry. These robots can be applied for various industrial applications such as the healthcare industry, industrial security, ocean and space exploration, the foodservice industry, and distribution applications. But modern industries have faced many difficulties due to accidental conditions such as fires. Prevention and pre-identification in such scenarios are the most discussed topic in modern science and technology. Detecting and extinguishing the emergency fire flame in less time duration is the most important factor in every industrial fire extinguishing system. This paper presents a novel approach to detect and extinguishes ground-level emergency fire flames in the industrial environment using vision feedback and a mobile robot. In this research, the image processing system and mobile robot are separate systems that contribute directly to detect and extinguish the emergency fire flames. Also, mainly focused on developing a fire detection algorithm to track the primary stage of emergency fire flames at ground level using properties of the HSV color space with a location identification algorithm. Cartesian coordinate mapping technique and mathematical operations have been applied for location identification. The four-wheeled mobile robot is operated on a wireless feedback signal to reach the desired location using a modified odometry concept with an error reduction coefficient. Fire detection results are further inspected by the flame sensors setup which is mounted on the robot body. Image processing feedback and flame sensor feedback combination have been applied to improve the accuracy of this fire robot in the industrial environment.

Multisensor fire detection algorithm (MSFDA) is one of the current important research issues for intelligent building. First, we design a fire fighting robot with extinguish for the intelligent building. The fire fighting robot is constructed using aluminium frame. The contour of the robot is cylinder. The diameter is 40 cm, and height is about 80 cm. There are six systems in the fire fighting robot, including structure, avoidance obstacle and driver system, software development system, fire detection, remote supervise system and others. We design the fire detection system using three flame sensors in the fire fighting robot. The adaptive fusion method is proposed for tire detection of fire fighting robot. We use computer simulation to improve the method to be adequate for fire detection. We design the fire detection system in the fire fighting robot, and program the tire detection and fighting procedure using sensor based method. Finally, we implement the fire detection system using fire fighting robot. If fire accident is true, the robot can find out fire source using the proposed method by fire detection system, and move to fire source to fight the fire using extinguish.

The security of home, laboratory, office, factory and building is important to human life. We develop an intelligent multisensor based security system that contains a fire fighting robot in our daily life. The security system can detect abnormal and dangerous situation and notify us. First, we design a fire fighting robot with extinguisher for the intelligent building. The fire fighting robot is constructed using aluminum frame. The contour of the robot is cylinder. The diameter is 50 cm, and height is about 130 cm. There are six systems in the fire fighting robot, including structure, avoidance obstacle and driver system, software development system, fire detection, remote supervise system and others. We design the fire detection system using two flame sensors in the fire fighting robot. We design the fire detection system in the fire fighting robot, and program the fire detection and fighting procedure using sensor based method. We design a low cost based obstacle detection modular using IR sensor and ultrasonic sensor in the robot. We think that man-machine interface in the fire fighting robot that must has mobility and convenience, we use touch screen to display system status, and design a general user interface (GUI) on the touch screen. Finally, we implement the fire detection system using fire fighting robot. If fire accident is true, the robot can find out fire source using the proposed method by fire detection system, and move to fire source to fight the fire using extinguish.

The overall results of this research addressed the question of how increased time for mineworkers to evacuate mines prior to the onset of untenable fire conditions is achievable. Additionally, improved asset loss control for underground mining is feasible through the successful development of Video Based Fire Detection (VBFD) in mining, as it provides more information earlier for mine fire fighters to intervene in the growth and spread of fire, therefore maintainable coal production is achievable. VBFD may also be used to activate automatic fire suppression systems. VBFD is an emerging volume type smoke detection technology that utilises Closed Circuit Television (CCTV) cameras to capture and analyse real time video data for the purpose of smoke recognition. VBFD technology performance was compared with the performance of fire detection methods currently used in underground coalmines to determine whether valuable improvements to fire safety and asset loss control could be made. Increased available safe evacuation time for mineworkers and a longer available time to extinguish fires earlier in their growth stage were considered the primary measures of success. The scope of this research included three main studies: a. Proof Of Concept (POC) tests; b. Detailed Experiments; and c. Field Testing. The initial trials successfully demonstrated the capability of VBFD to detect small coal fires associated with fixed plant installations in a low light simulated mine environment. Encouraged by these findings, detailed experiments were developed and subsequently applied at the Safety In Mines Testing and Research Station (SIMTARS) experimental facility at Redbank, Australia. The experimental plan involved 54 individual fire test experiments that recorded the level of Carbon Monoxide (CO) concurrent at the VBFD alarm activation time. Sensitivity analysis was undertaken by varying the air velocity over the fire source, which affected the smoke plume shape. The other component of the sensitivity analysis involved variations in light levels aimed at testing the VBFD smoke detection sensitivity. The data were subsequently analysed to identify trends in the detection response of both the CO sensors and the VBFD. Some of the tests carried out exceeded the capability of the VBFD system, which was an important aspect in the research and the evolving capability of video smoke detection. The experimental fire characteristics were subsequently replicated numerically using Computational Fluid Dynamics (CFD) so it could be used in this research to estimate the evacuation response of mineworkers under more onerous fire conditions, which could not physically be undertaken in an operational mine. A following VBFD field study was proposed to review and utilise the results of installation commissioning data and maintenance testing of a VBFD system at an operational underground mine environment. The purpose of this field-testing was to inform the underground mining industry of limitations that may exist in terms of the VBFD reliability in service, such as potential maintenance issues. During the period of the subject research the Australian resources industry moved from being in a position to readily facilitate and support minor external unfunded research projects within its underground mine assets, to its current position where it was no longer willing or able to assist. As a result of the lack of a trial VBFD system in an underground mine, the subsequent field study opportunistically considered the reliability and performance of VBFD in a very similar and related environment, however this facility was not an underground mine, but a South African coal fired power station. The results of the reliability testing of 360 VBFD devices over a 12 months’ period showed that VBFD was very reliable. Future VBFD research might address two aspects. Firstly, VBFD may be used to detect flames or smoke. Whilst coal handling plant fires typically manifest during their early stages of growth as smouldering fires, other fixed plant fires have the potential to produce flames from the outset. Underground refuelling stations and transformers exhibit this phenomenon, so flame detection capability is possible and should be explored. In this research, VBFD CCTV cameras were of a very basic functionality. They were simple, relatively low cost devices operating in the visible light spectrum only. Secondly, the use of high resolution “mega pixel” cameras with the capability to operate in very low light levels should be researched. It was found that VBFD offers considerably faster response to visible smoke plumes than other forms of fire detection currently used in underground coalmines. In terms of VBFD reliability, it was more resistant to contamination from mine pollutants than typical commercial ‘point type’ photoelectric or ionisation smoke detectors. It was shown in the research that significant improvements in fire safety and asset loss control in underground mining can be made through the application of VBFD for early fire detection of fixed plant fires.

Fire accidents occur frequently in highway tunnels, and the process of fire source from generation to disaster in tunnels is very fast. It is of great significance to set fire detectors in highway tunnels to improve fire control ability, so as to ensure the safety of life and property. At present, there is still some phenomenon of failing to report or false alarm for fire detectors, and the sensing parameters and installation location of fire detectors need to be determined based on the spatial distribution pattern of fire sources to give full play to their accurate sensing function. In this paper, the spatial distribution pattern of potential fire sources in road tunnels is systematically revealed from the vehicle, road and tunnel facilities aspects, and the area within 1.5m of the tunnel headroom from the road surface is found to be the most concentrated high-risk area for potential fire source distribution. Finally, the layout of fire source sensing equipment in the high-risk areas of the tunnel and the suggestions for the emergency management of tunnel fire source sensing are put forward.

LES analysis of fire source aspect ratio effects on fire-wind enhancement

The present state of research on toxicities of fire effluents in Japan is described. This review centers on the status of a joint study project which has been under way in recent years, participated in by research institutions in the country. The research setup in the country, the method of applying conditions of actual fires to testing apparatus of laboratory scale, the role of CO, mixed with pure gases, and the results of square wave exposure of fire effluents in a newly developed testing apparatus are described.

The temperature field characteristics of highway tunnels during fire conditions are investigated in this paper. Numerical simulations coupled with reduced-scale physical model tests were conducted to analyze the thermal characteristics of the tunnel interior and lining structure under various ventilation conditions. Taking the extra-long double-tube highway tunnel as a case study, a numerical model was established using FLUENT to simulate a 100 MW fire under different longitudinal ventilation velocities. Furthermore, a reduced-scale physical model with a geometric similarity ratio of 1:2.7 was fabricated to investigate the effect of lining moisture content on the heat transfer characteristics. It is indicated by the results that high-temperature zones above 800 °C are mainly concentrated within roughly 100 m of the fire source, extending approximately 20 m upstream and 80 m downstream. As the ventilation velocity rises, the high-temperature zone adjacent to the fire source is gradually reduced, the upstream smoke backflow length is shortened, and the downstream thermal influence range is expanded. Obvious spatial variations are observed in the cross-sectional temperature distribution: relatively uniform temperatures are found near the fire source, whereas higher temperatures are observed at the crown in upstream and downstream sections, followed by the haunch and sidewalls. A pronounced thermal lag effect is observed in the lining structure, with both slower heating rates and lower peak temperatures being exhibited at larger distances from the fire source and in linings with higher moisture content. A temperature plateau at around 100 °C is detected, which is mainly attributed to latent heat absorption during moisture evaporation. A more significant temperature gradient through the lining thickness is also caused by a higher moisture content. These findings provide valuable references for tunnel fire safety design, smoke control strategies, and evacuation safety analysis.

<span>This article proposes a security system which detects the fire events and plans the moving route. Each robot with several modules owns the shape of cylinder and height, weight and diameter is 18</span><span>cm, 1.5</span><span>kg and 8</span><span>cm. A main controller (STC12C5A60S2) equips robots as a microprocessor. Each robot has the capability to escape from the fire scene. Whenever detecting fires and obstacles using image sensor and reflective IR sensors, robots send the ID code, orientation, and position to the centralized computer and other robots. After other robots have confirmed the fire events, the centralized computer uses the Gaussian probability function to calculate the danger values of the surrounding points near the fire source. And Bayesian estimation method is applied to compute the total estimated value of each point in platform. Furthermore, the total weighted values of all points are shown in a platform and its aim is to enlarge the difference between danger and safety without ambiguity. A* algorithm is used in the escaping routes are planned by a centralized computer. The mobile robot follows the leading of the supervised computer autonomously to escape from dangerous areas. The air-fuel ratio and the rate of increasing in temperature with distance are directly proportional to the danger value. Associating the increasing temperature rate with three-fire sources, it is verified to be an efficient system.</span>

This research proposes a multi-layer navigation system for indoor mobile robots when they share space with vulnerable individuals. The primary objectives are increasing or maintaining safety measures and curtailing operational costs, emphasizing reducing reliance on intricate sensor technologies and computational resources. The developed system employs a three-tiered control approach, with each layer playing a pivotal role in the navigation process. The "online" control layer integrates a human-in-the-loop strategy, where the human operator detects missing obstacles or approaching danger through a user interface and sends a trigger to the robot's controller. This trigger enables the system to estimate the coordinates of the danger and update the robot's navigation path in real time, minimizing reliance on complex sensor systems. The "semi-online" control layer generates dynamic virtual barriers to restrict the robot's navigation in specific areas during specific times. This ensures the robot avoids hazardous zones that could pose temporary risks to the human or robot. For example, areas with temporary obstructions or potential danger, such as kids' play zones or during cleaning, are temporarily restricted from the robot's path, ensuring safe navigation without relying solely on real-time sensor data. The "offline" control layer centers around the use of semantic information to control the robot's behavior according to user-defined space management and safety requirements. By leveraging Building Information Models (BIM) as digital twins, this layer combines semantic and geometric data to comprehensively understand the environment. It enables the robot to navigate according to precise user requirements, utilizing the semantic context for path planning and behavior control. This layer obviates the need for a real-time sensor mapping process, making the system more efficient and adaptable to user needs. This research represents a significant step forward in enhancing the navigational capabilities of robots within human-centric indoor environments, with a core focus on safety, adaptability, and cost-effectiveness.